Maliheh Aramon

Hi Peizan, Since version 9, the Gurobi Optimizer supports solving models with noncovex quadratic objective function (see “What types of models can Gurobi solve?”). You need to build your model usin...

Are there any speed or other operational benefits to modifying a prebuilt model vs building a new one?This depends on how many changes are needed to derive the modified model from the existing one....

Hi Ryan, I assume that the time required to build a model for a given dataset is relatively small. Therefore, it would be better to re-write your script so that it takes the data as input and retur...

Hi Lene, In general, we say that the barrier converges when the normalized duality gap and normalized complementary slackness are within the BarConvTol parameter value. However, the actual terminat...

Hi Pedro, Does a quadratic objective function affect the convexity of the model?Yes, a quadratic objective function is not necessarily convex. For instance, the quadratic objective \(x_1^2 - x_2 ^2...

Hi Miroslav,Gurobi does not currently support direct optimization of black-box functions. If relevant, you can use the Gurobi Machine Learning Package to embed a trained regression model within a g...

I am still struggling to understand what p and q really mean in your optimization problem. It is hard for me to comprehend your problem as an optimization problem. Just focusing on this constraint:...

Hi Huib, How should the constraints look like for the scenarios where p = 0 and/or q = 0?Do you want to model the constraints below?If p = 0, then q = 0 and r = 1If this is the case, you should add...

Hi Ramesh, Gurobi can directly solve ILPs, so there is no need to manually convert them to LPs. The underlying solution methodology for solving an ILP is called branch-and-bound which is an LP-base...

Hi Ignacio, The behavior you're observing can occur when the model is prone to numerical issues, as you alluded to. In such cases, the "optimal" solution obtained may not be of perfect quality. The...